Publications by authors named "Junyuan Zhong"

Purpose: This study aims to assess whether the novel CovBat harmonization method can further reduce radiomics feature variability from different imaging devices in multi-center studies and improve machine learning model performance compared to the ComBat method.

Materials: Non-contrast abdominal CT scans of 1,000 healthy subjects from three medical institutions (from four manufacturers and eight different models) were retrospectively included: Hospital A (n = 513), Hospital B (n = 338), and Hospital C (n = 149). 93 radiomics features were extracted from liver and spleen tissues using PyRadiomics.

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Objectives: To evaluate the value of contrast-enhanced CT in diagnosing ultrasonography-unspecified adnexal torsion (AT).

Methods: Surgically confirmed patients with painful pelvic masses (n = 165) were retrospectively collected from two institutes. Two senior radiologists independently reviewed the CT images and determined the Hounsfield unit difference between non-contrast vs portal venous phases (ΔHU) in both derivation and validation samples.

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Rationale And Objectives: To develop an automatic deep-radiomics framework that diagnoses and stratifies prostate cancer in patients with prostate-specific antigen (PSA) levels between 4 and 10 ng/mL.

Materials And Methods: A total of 1124 patients with histological results and PSA levels between 4 and 10 ng/mL were enrolled from one public dataset and two local institutions. An nnUNet was trained for prostate masks, and a feature extraction module identified suspicious lesion masks.

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Objective: Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5DM-ILD) often leads to acute respiratory failure and endangers lives. This study quantitatively analysed chest high-resolution computed tomography (HRCT) images to assess MDA5DM-ILD and establish a risk prediction model for severe ILD within six months.

Methods: We developed a 'Standardized Threshold Ratio Analysis & Distribution' (STRAD) to analyse lung HRCT images.

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Objective: The aim of this study was to investigate the clinical, imaging and pathological features of extraskeletal osteosarcoma (EOS) and to improve the understanding of this disease and other similar lesions.

Methods: The data for 11 patients with pathologically confirmed extraosseous osteosarcoma, including tumour site and size and imaging and clinical manifestations, were analysed retrospectively.

Results: Six patients were male (60%), and 5 were female (40%); patient age ranged from 23 to 76 years (average age 47.

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Background: Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of non-small cell lung cancer (NSCLC) but differs in terms of treatment strategies compared with conventional-NSCLC (c-NSCLC). However, preoperative CT differentiation between PSC and c-NSCLC remains a challenge. This study aimed to explore the CT findings and prognosis of PSC compared with c-NSCLC of similar tumor size.

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Aims: Nonvalvular atrial fibrillation often occurs in combination with carotid atherosclerosis, but less is known about it in combination with cerebral artery stenosis. This study investigated the characteristics of cerebral infarction in patients with nonvalvular atrial fibrillation with or without cerebral artery stenosis.

Methods: A retrospective analysis was conducted on 172 cerebral infarction patients with nonvalvular atrial fibrillation hospitalized at the Affiliated Ganzhou Hospital of Nanchang University between December 2011 and January 2016.

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Background: Tandem mass spectrometry (TMS)-based newborn screening has been proven successful as one of the public healthcare programs, although the practicability has not yet been specifically addressed.

Methods: Sixty residual dried blood spot (DBS) specimens from confirmation/diagnosis-insufficient cases discovered by TMS screening were analyzed by targeted next generation sequencing (TNGS) assay.

Results: In total, 26, 11, 9, and 14 cases were diagnosed as positive, high risk, low risk, and negative, respectively.

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